AI can make work considerably easier. At the same time, it can get the user to the destination without them fully understanding the route they took. That is why ChatGPT reminds me of both an automatic transmission and a satnav – in two completely opposite ways.
Over the past year, I have become thoroughly fascinated by AI.
During the past few weeks, I have used ChatGPT to build an entire website for Sulonen Solutions, plan its structure and content, and write Gutenberg code and CSS definitions. I have developed my own booking module and used Codex to build a Mac application. Among other things, the app monitors the computer’s temperatures and memory usage.
Not long ago, I would never have imagined doing these things myself.
Or wait a minute – did I actually do them myself?
“Oh, ChatGPT built your website?”
This is probably one of the most common comments related to the use of AI:
“Oh, ChatGPT built your website? Then you didn’t really build it yourself.”
It is an interesting question, because by the same logic, a large part of modern work is no longer done by people themselves.
Did you write the report yourself even though you used Word?
Did you make the calculation yourself even though Excel added up the figures?
Did you take the photograph yourself even though the camera focused automatically?
Did you build the piece of furniture yourself even though you used a power drill?
Did you drive from Vantaa to Helsinki yourself even though your car had an automatic transmission?
That last comparison probably describes my own experience of using ChatGPT best.
An automatic transmission does not drive the car for me
I learned to drive in a manual car. It is still a useful skill, and when necessary, I can change gears myself.
Today, however, automatic transmissions are so good, unobtrusive and comfortable that I can think of very few reasons why I would insist on using a manual gearbox in ordinary traffic.
The automatic transmission handles one part of driving for me. At the same time, I have more capacity to monitor traffic, observe my surroundings and focus on driving itself.
It does not, however, decide where I am going.
If I drive from Vantaa to Helsinki, I decide to make the journey. I have a reason to get to Helsinki. I choose the destination, steer the car, monitor the traffic and take responsibility for the decisions I make.
Nobody says after the journey:
“You didn’t drive to Helsinki yourself. The automatic transmission made the trip.”
No, it did not.
I drove. The automatic transmission made the journey I had chosen easier and more comfortable.
In the same way, ChatGPT did not decide to establish Sulonen Solutions. It did not define the company’s services, objectives or client promise. It did not know what the website should look like or what kind of impression I wanted the company to create.
I defined the objective.
I evaluated the suggestions.
I approved, rejected and requested changes to the solutions.
I decided when the result was good enough and when the work still needed to continue.
ChatGPT and Codex made the implementation faster. They removed technical barriers and helped me do things for which I would previously have needed several different specialists.
In this sense, AI is an excellent automatic transmission.
But the comparison has another side as well.
A satnav can get you there without teaching you the route
While building the website, I sometimes worked with ChatGPT in very small steps.
I received a short instruction. I carried it out in WordPress and took a screenshot.
ChatGPT checked the image and gave me the next instruction.
I carried that out as well and sent another screenshot.
This is how we proceeded, step by step, for several hours.
At some point, I noticed something strange: I was no longer entirely sure which stage of the overall project we were in or what we had already changed.
I had focused carefully on each individual instruction, but keeping track of the bigger picture had received less attention.
Exactly the same thing can happen when using a satnav.
The satnav says:
Turn right at the next junction.
Continue for 300 metres.
Take the second exit at the roundabout.
By following the instructions, you will usually reach your destination efficiently. But if someone asks afterwards which route you took, answering can be surprisingly difficult.
You did not follow the city, the compass directions or the overall route. You followed only the next instruction.
If you make the same journey without a satnav, you have to understand the route differently. You pay attention to roads, junctions, landmarks and the direction in which the destination lies.
The journey may require more concentration, but at the same time, you learn the route.
The same thing can happen with AI.
You can follow a long series of perfectly correct instructions and eventually end up with a functioning system. That does not automatically mean that you understand how the system works.
Did you merely arrive, or did you also learn the route?
When using AI, it is therefore not enough to ask only:
“What should I do next?”
Sometimes you also need to stop and ask:
- What have we built so far?
- Why was this solution implemented in this particular way?
- How do the different parts relate to one another?
- What changes have been made, and to which files?
- What are the risks and dependencies of the solution?
- What happens if one part stops working?
- Could I explain the whole system to another person?
I learned this during my own website project as well.
Once enough stages had accumulated, simply following the next instruction was no longer sufficient. We needed summaries, documentation, code clean-up and a fresh understanding of the whole.
In other words, sometimes I had to stop following the satnav and open the map.
AI should be used – not obeyed
The greatest benefit of a tool like ChatGPT does not come from giving the user an endless stream of instructions.
The benefit comes from the human being knowing how to lead the collaboration.
You need to be able to tell the AI:
- what is being done
- why it is being done
- what kind of outcome is wanted
- what constraints need to be considered
- how success will be evaluated
In addition, the user needs to be able to recognise when a suggestion does not match the objective.
AI can write technically functional code that still does not fit the wider system. It can suggest impressive content that does not match the company’s tone of voice. It can solve one problem in a way that creates three new ones later.
That is why responsibility does not transfer to AI.
A good driver makes use of the car’s features but continues to monitor the traffic.
A good satnav user listens to the directions but also checks the full route from time to time.
A good AI user takes advantage of the tool’s speed and expertise but does not surrender decision-making authority or responsibility to it.
What if AI did part of the work?
Of course it did.
That is exactly why I used it.
I do not use technology to prove that I can do everything in the most difficult way possible. I use it to achieve a better result faster and more sensibly.
In business, it should ultimately be fairly irrelevant how many times someone pressed the space bar or whether they wrote every line of code by hand.
Far more important questions are:
- Did the work solve the right problem?
- Was the outcome good?
- Did it save time or money?
- Did someone understand the whole?
- Was the outcome checked?
- Who made the decisions?
- Who carries the responsibility?
If AI helps one person do things that previously required an entire team, it does not reduce the value of that person’s work.
It changes the nature of the work.
Alongside technical execution, greater emphasis is placed on defining objectives, understanding complex systems, making decisions, evaluating quality and asking the right questions.
Those are also core leadership skills.
Use the automatic transmission, but do not lose the map
I am happy to use an automatic transmission. I do not need to prove to anyone that I know how to change gears manually.
I am also happy to use a satnav. Even so, I sometimes want to look at the map and understand where I am and where I am going.
That is how I want to use AI as well.
I want to take advantage of the speed, ease and opportunities it offers. But I do not want to surrender my own judgement, my understanding of the whole or my responsibility for the outcome.
AI can make the journey considerably easier.
But the human being still has to decide where we are going – and keep their hands on the wheel.